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A Sensorized Mechanically Self-Guided Suction Cup for Improved Adhesion in Complex Environments
Feiyang Yuan1, Lufeng Tian1, Haoyuan Xu1
1School of Mechanical Engineering and Automation, Beihang University, Beijing, China.
None:
Octopuses can effectively interact with environments using their agile suction cups, in which abundant neuroreceptors are embodied inside. Inspired by this, we proposed an electronics-integrated self-guided adhesive suction cup (E-SGAS) capable of environmental sensing and adaptively adhesion on diverse surfaces. E-SGAS features an inflatable adhesive membrane and an under-actuated design, enabling it to adapt to various angles and surface roughness under low preloads. A theoretical model is presented to predict self-guided adhesion outcomes. The integrated multilayer stretchable liquid metal sensory circuit (with a maximum deformation rate of 186%) in the adhesive membrane allows for detecting expansion, contact, suction, leakage, and surface roughness. E-SGAS can also process the sensory information to guide intelligent gripping in various complex environments. Experimental results demonstrate the ability of E-SGAS to autonomously grip under a preload force of 0.11 N, a maximum adhesion force of 57.9N, and a detachment force of only 0.34 N. It can adhere to surfaces up to 60-grit roughness and accommodate a surface with a relative angle of 90°. We also show that E-SGAS can capture flying objects or work in a confined space. The proposed adhesion and sensing strategies aim to enhance the performance and expand the application range of suction cup-like grippers. E-SGAS's results can provide design insights into creating stretchable electronics-integrated bioinspired adhesive systems that can interact with unconstructed environments.

